With climate change effects on the rise, it is of great importance to be aware of any new challenges and know how to handle them. One of the consequences that have resulted is an increasing amount of fires globally. An analysis felt warranted using fire occurrences found in the US, narrowed down to Colorado to determine what insights can be made with the data that’s been gathered so far.
After pulling the data, some questions naturally arose: * Which district had the most fires? * Which districts had the longest burning fires? * What months have a higher chance of a fire occuring?
Using data analysis techniques in QGIS and python, we are able to see the results in an attempt to answer these questions.
Looking into the data.colorado.gov website, there seems to be several districts available to choose from. The two that stood out while navigating the data catalog were these:
Fire Districts in Colorado
Parks and Rec Districts in Colorado
To test out the capabilities of the QGIS interface, an intersection of the two layers was performed.
Fire/Parks and Rec District Intersection
This looks mostly the same as the Parks and Rec layer as expected, save a couple of areas. This is because the fire district seems to span quite a larger area of the state, and the fact that logically it makes sense that the fire district overlaps the Parks and Rec district quite a bit. What is neat is that we can take the same intersection and only find the fires that fall within this layer.
The fire occurences data happened to contain an attribute table, which has an occurence date as a column. Using this, the temporal feature within QGIS generated slides, which a gif could be created. The result: